This study investigates the impact of uncertainty and volatility on ten Islamic stock returns using monthly data for from 2011:M5 to 2021:M5. We rely on the continuous wavelet transform and wavelet coherence ratios, which allows decomposition of time series across time scales to investigate the causal relationship between stock market returns, economic policy uncertainty and volatility. Our results provide some interesting insights. First, economic policy uncertainty, in general, has a negative effect on the majority of Islamic stock returns, except for the Dow Jones Islamic Market (DJIM). Second, volatility has a significant positive impact on most of the Islamic stock returns in various countries. Third, both economic policy uncertainty and volatility have a greater impact on the Islamic stock returns post-COVID-19 outbreak. These results should assist investors to re-evaluate their portfolios to fully maximize the potentials of these Islamic stock markets. Policymakers could use these results to design policies to reduce economic policy uncertainty as well as to cushion the impact of externally generated uncertainties.

In the present paper, we show how uncertainty emanating from fluctuations in economic uncertainty, news-based uncertainty, and geopolitical risks affect the number of containers exported from Thailand via Penang Port, Malaysia. Our sample extends from January 2009 to May 2020 from three main entry points in the Northern Peninsular Malaysia–Thailand Border: Padang Besar, Surat Thani, and Bukit Kayu Hitam. Two modes of transportation of containers are mainly used for export purposes, namely, road and rai. This study examines the nonlinear effect of uncertainty on trade by employing a two-regime Markov regime-switching approach. The empirical results show that, overall, uncertainty significantly affects the movement of containers in the high-uncertainty regime. Therefore, small ports must continue to diversify their client base to cushion the impact of fluctuations in global trade due to uncertainty.

Environmental pollution is a major global challenge that can adversely affect ecosystems and human health. In developing countries, the lack of awareness and inadequate sustainable practices exacerbate pollution levels, making it imperative to identify long-term solutions. Here, education plays a crucial role in addressing this issue by raising environmental awareness, encouraging sustainable practices, and shaping policy reforms. Despite the importance of education in driving environmental change, the precise impact of education levels and expenditures on reducing pollution remains underexplored, especially in the ASEAN region. This paper addresses this issue by examining how education mitigates environmental pollution, focusing on both the level of education and expenditure on education. Using data from ten ASEAN countries covering the period from 1980 to 2022, this study employs three statistical methods—quantile regression (0.5), FMOLS, and Robust OLS—to analyze the relationship between education and CO2 emissions. The results consistently show a negative relationship between CO2 emissions and education, as measured by educational expenditure in primary, secondary, and tertiary education. These findings suggest that investing in education, regardless of the level, has a significant and direct impact on reducing CO2 emissions. By fostering a well-educated and environmentally aware population, ASEAN countries can achieve substantial reductions in CO2 emissions, contributing to global efforts to reduce environmental pollution.

The purpose of this study is to investigate the impacts of calendar anomalies specifically on day of the week effect (DOW) on 10 Islamic stock markets’ returns such as Dow Jones Islamic Market (DJIM), Saudi Arabia, Malaysia, United Arab Emirates (UAE), Kuwait, Qatar, Turkey, Indonesia, Bahrain, Pakistan—for 20 years from 25 September 2000 to 24 September 2020. The methods of study using Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) and Exponential Generalized AutoRegressive Conditional Heteroskedasticity (EGARCH) as a robustness test. The findings revealed that calendar anomalies had considerable impacts on returns for the following Islamic stock markets: DJIM, Indonesia, and Pakistan.